ArticleCancer biomarkers : section A of Disease markers2023
The association between pain and WHO grade of pancreatic neuroendocrine neoplasms: A multicenter study.
Article in Cancer biomarkers : section A of Disease markers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Mechanism of LDH and IL-8 involved in pancreatic cancer pain and the correlation of pain degree.Journal of medical biochemistry · 2024Article
- The association between jaundice and poorly differentiated pancreatic neuroendocrine neoplasms (Ki67 index > 55.0%).BMC gastroenterology · 2023Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAbdominal or back pain is a common symptom in pancreatic diseases. However, the role of pain in pancreatic neuroendocrine neoplasm (PNENs) has not been clarified.
objectiveIn this study, we aimed to show the association between the pain and the grade of PNENs.
methodsA total of 186 patients with pathologically confirmed PNENs were included in this study. Clinical features and histological or radiological findings (size, location, and vascular invasion and local organs invasion and distal metastasis) were collected. Logistic regression analyses were used to show the association between pain and grade of PNENs. Nomogram was developed based on associated factors to predict the higher grade of PNENs. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of size and nomogram model.
resultsThe prevalence of pain in the cohort was 30.6% (n= 57). The vascular invasion and G3 PNENs were more common in the pain group (P= 0.02, P< 0.01). The tumor size was larger and incident of higher grade of PNENs was higher in the pain group than the non-pain group (p< 0.01). Age, pain and size were independent risk factors for G2/G3 or G3 PNENs. The odds ratio was 3.03 (95% CI: 1.67-7.91) and 3.32 (95% CI: 1.42-7.79) for pain, respectively. The nomogram model was developed to predict the G2/G3 or G3 PNENs. The area under the curve (AUC) of the nomogram model was 0.84 (95% CI, 0.77-0.91) in predicting the G2/G3 PNENs, and was 0.84 (95% CI, 0.78-0.91) in predicting the G3 PNENs.
conclusionAbdominal or back pain is associated with the grade of PNENs. The nomograms based on clinical features may be a powerful numerical tool for predicting the grade of PNENs.
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